Automated license plate recognition (hereinafter, “ALPR”) generally refers to an automated process for applying optical character recognition (hereinafter, “OCR”) techniques to images captured by traffic cameras to recognize vehicle license plate information.
ALPR technology is useful for law enforcement and other purposes, allowing for mass surveillance of vehicle traffic for a variety purposes at very low personnel costs. ALPR technology can be utilized concurrently with a variety of law enforcement procedures, such as techniques for determining vehicle speed, monitoring traffic signals, electronic toll collection, and individual vehicle surveillance.
ALPR methods can involve three steps. The first step can be determining the location of the license plate in the image (hereinafter, “plate localization”). The second step can be separating the individual characters on the license plate from the remainder of the image (hereinafter, “character segmentation”). The third step can be applying OCR techniques to the segmented characters.
The challenge for character segmentation is to provide a robust, highly accurate solution that is also computationally efficient. Accordingly, to minimize computational load and reduce extraneous noises present in captured images, it is common to identify a tight bounding box sub-image (hereinafter, “tight bounding box” or “TBB”) that surrounds the license plate characters prior to character segmentation.
However, extracting a tight bounding box sub-image can be a challenging task due to variations in image quality, noise, tilt of captured license plate images, etc.
Accordingly, APLR technology may be improved by techniques for efficiently identifying and/or extracting a tight bounding box that surrounds license plate characters in a captured image.